CS 525W: Mobile Ubiquitous Computing and Wireless Networking - - PowerPoint PPT Presentation

CS 525W: Mobile Ubiquitous Computing and Wireless Networking

Emmanuel Agu

A Little about me

• Faculty in WPI Computer Science
• Research interests: graphics, mobile computing/wireless and

mobile graphics g p

• How did I get into mobile computing + wireless?

– 3 years in wireless LAN lab (pre 802.11) Designed simulated implemented wireless protocols – Designed, simulated, implemented wireless protocols – Group built working wireless LAN testbed (pre 802.11)

• Computer Systems/Electrical/Computer Science background
• Hardware + software

About this class (Administrivia)

• Class goal: provide overview, insight into hot topics, ideas and

issues in mobile ubiquitous computing and wireless networking

• Full course name: Mobile Ubiquitous Computing and Wireless

q p g Networking

• Meet for 14 weeks, break on March 8 (term break)
• Seminar style: I will present YOU will present papers

Seminar style: I will present, YOU will present papers

• See big picture through focussed discussions
• Check for papers on course website:

http://web cs wpi edu/ emmanuel/courses/cs525m/S11/ http://web.cs.wpi.edu/~emmanuel/courses/cs525m/S11/

• Projects: 1 or 2 assigned, 1 big final project
• This area combines lots of other areas: (networking, OS, software,

h l ) M l d ’ h ll h b k d!! machine learning, etc): Most people don’t have all the background!!

• Projects: Make sure your team has requisite skills

Administrivia: Papers

• Weeks 1 and 2: I will present
• Weeks 2 – 12: You will present + I will present

– I will present background material on the week’s topic I will present background material on the week s topic – 3 student presentations from Required Papers for the week

• Student presentations: ~30 mins + ~10 mins discussion

15 b k h lf h h h d

• 15-min break halfway through each day

Formal Requirements

• What do you have to do to get a grade?
• Seminar: Come to class + Discuss!! Discuss!! Discuss!!
• Present 2 or 3 papers

Present 2 or 3 papers

• Email me 1-page summaries (in ASCII text) for weekly papers
• Do assigned project(s)

D 5 h

• Do term project: 5-phases

– Pick partner + decide project area – Submit intro + related work Propose project plan – Propose project plan – Build, evaluate, experiment, analyze results – Present results + submit final paper (in week 14)

• Grading policy:Presentation(s): 30% Class participation: 10% Final

Grading policy:Presentation(s): 30%, Class participation: 10%, Final project: 50%, Summaries: 10%.

Written Summaries

• Email to me before class in ASCII text. No Word, Latex, etc
• Summarize key points of all 3 papers for week
• Main contributions

Main contributions

• Limitations of the work
• What you like/not like about paper
• Any project ideas?

Any project ideas?

• 20 sentences max per paper
• Summary is quick refresh in even 1 year’s time

I l d i id / l ith lt t

• Include main ideas/algorithms, results, etc.
• See handout for more details

Students: Please Introduce Yourselves!

• Name
• Status: grad/undergrad, year
• Relevant background: e g coal miner 

Relevant background: e.g. coal miner 

• Relevant courses taken:
• Systems: Networks, OS,
• Ad anced: machine learnin ad anced net

rks etc

• Advanced: machine learning, advanced networks, etc
• What you would like to get out of this class?

– Understanding a hot field J l f d /PhD – Just a class for masters degree/PhD – Compliments your research interests/publications – My spouse told me to 

Next… Overview

• Brief overview of topics/issues
• Define/motivate area, excite (or discourage) you
• Provoke thinking: More questions problems than solutions

Provoke thinking: More questions, problems than solutions

• Sample of topics to be covered in class
• ALL topics covered in more detail later

S d l d d f d ’

• Students may only understand part of topics in today’s overview

Mobile computing

M k W i X PARC CTO

• Mark Weiser, Xerox PARC CTO
• 1991, articulated vision (and issues) for ubiquitous mobile computing
• Weiser’s Vision:

“Environment saturated with computing and communication capabilities, with humans gracefully integrated”

• Core idea: Invisible hardware/software that assist human
• Hardware: smart phones, sensors, tablets, wearable devices, etc
• Software: Voice recognition Mobile OS Networking/communication
• Software: Voice recognition, Mobile OS, Networking/communication

software, protocols, etc

• Weiser’s vision ahead of its time, available hardware and software
• Example: voice recognition was not available then
• Example: voice recognition was not available then
• Today, envisioned hardware and software is available

Mobile vs Ubiquitous Computing

• Mobile computing
• deals mostly with passive network components
• Human simply provided universal, seamless network connectivity

p y p , y

• Human does all the work, initiates all activity, network traffic!!
• Example: Using foursquare.com on smart phone
• Ubiquitous computing

Ubiquitous computing

• introduces collection of specialized assistants to assist human in tasks

(reminders, personal assistant, staying healthy, school, etc)

• Networked array of active elements, sensors, software agents,

y , , g , artificial intelligence

• Builds on distributed systems and mobile computing (more later)

Ubicomp Sensing

• Sense what?

– Human: motion, mood, identity, gesture – Environmental: temperature sound humidity location Environmental: temperature, sound, humidity, location – Ubicomp example:

• Assistant senses: Temperature outside is 10F

(environment sensing) + Human plans to go work (environment sensing) + Human plans to go work (schedule)

• Assistant advise: Dress warm!

S d H C C

• Sensed environment + Human + Computer resources = Context
• Context-Aware applications adapt their behavior to context

Sensing the Human

• Environmental sensing is relatively straight-forward to integrate
• Human sensing is a little harder (ranked easy to hard problems)

– Where: location (easiest): Where: location (easiest): – Who: Identification – How: (Mood) happy, sad, bored (gesture recognition) – What: eating cooking (meta task) What: eating, cooking (meta task) – Why: reason for actions (extremely hard!)

• Human sensing (gesture, mood, etc) easier with cameras than

sensors sensors

• Research in ubiquitous smart environments (office, kindergarten)

integrates location sensing, user identification, emotion sensing, gesture recognition activity sensing user intent gesture recognition, activity sensing, user intent

Mobile Devices

• Smart phones (Blackberry, iPhone, Android, etc)
• Personal Digital Assistants (PDAs)
• Tablets (iPad, etc)
• Laptops

Mobile Devices: Droid

• This class: Google Droid as main mobile device
• Google donated Motorola Droid smart phones
• One assigned project and final project based on Droid
• Connects to Verizon network, WLAN or Bluetooth
• Google Android OS

Google Android OS

• 5 MegaPixel camera
• Streaming video: mpeg, H.264

GPS l t

• GPS, google maps, etc
• Sensors: accelerometer, proximity

eCompass, ambient light

Sensor Node

• Sensor? Think of automatic doors
• Automatic door sensor has single purpose: detect human
• New multi-functional sensors, programmable for various tasks

(intrusion detection, temperature, humidity, pressure, etc) ( , p , y, p , )

• Low cost ($1 per sensor), 1000’s per room, attach to objects
• Capabilities: Sense, process data, communicate with sink node
• Constraints: Small CPU OS programmable
• Constraints: Small CPU, OS, programmable

(courtesy of MANTIS RFID tags Tiny Mote Sensor, project, U. of Colorado) g y , UC Berkeley

Wireless Sensors for Environment Monitoring

• Embedded in room/environment
• Many sensors cooperate/communicate to perform task
• Monitors conditions (temperature humidity etc)

Monitors conditions (temperature, humidity, etc)

• User can query sensor (What is temp at sensor location?)

Ubiquitous Computing: Wearable sensors for Health

Explosion of Devices

• Recent Nokia quote: More cell phones than tooth brushes
• Many more sensors envisaged
• Ubiquitous computing: Many computers per person

Ubiquitous computing: Many computers per person

Worldwide cellular subscriber growth

Definitions: Portable, mobile & ubiquitous computing

• Distributed computing: system is physically distributed. User can

p g y p y y access system/network from various points. E.g. Unix, WWW. (huge 70’s revolution)

• Portable (nomadic) computing: user intermittently changes point
• f attachment, disrupts or shuts down network activities

M b l

• Mobile computing: continuous access, automatic reconnection
• Ubiquitous (or pervasive) computing: computing environment

i l di d i d i l h including sensors, cameras and integrated active elements that cooperate to help user

• Class concerned mostly with last 2 (mobile and ubiquitous)
• Class concerned mostly with last 2 (mobile and ubiquitous)

Distributed Computing

• Distributed computing example: You, logging in and web surfing

from different terminals on campus. Each web page consists of hypertext, pictures, movies and elements anywhere on the internet.

• Note: network is fixed, YOU move
• Issues:

– Remote communication (RPC), Remote communication (RPC), – Fault tolerance, – Availability (mirrored servers, etc) – Caching (for performance) Caching (for performance) – Distributed file systems (e.g. Network File System (NFS) – Security (Password control, authentication, encryption)

Nomadic computing

• Nomadic computing… Nomads… ?

Nomadic Computing

• Portable (nomadic) computing example: I own a laptop. Plugs

( ) p g p p p g into my home network, sit on couch, surf web while watching TV. In the morning, wake up, un-plug, shut down, bring laptop to school, plug into WPI network, start up!

• Note: Network is fixed, device moves and changes point of

attachment.

• Issues:

– File/data pre-fetching – Caching (to simulate availability) – Update policies Update policies – Re-integration and consistency models – Operation queuing (e.g. emails while disconnected) – Resource discovery (closest printer while at home is not closest printer Resource discovery (closest printer while at home is not closest printer while at WPI)

• Note: much of the adaptation in “middleware” layer

Mobile Computing Example

• Mobile computing: Sarah owns SPRINT PCS phone with web

access, voice, SMS messaging and can run apps like facebook and foursquare . She remains connected while she drives from Worcester, Massachusetts to Compton, California

• Note: Network topology changes, because sarah and mobile users
• move. Network deals with changing node location
• Issues

– Mobile networking (mobile IP, TCP performance) – Mobile information access (bandwidth adaptive) ( p ) – System-level energy savings (variable CPU speed, hard disk spin-down, voltage scaling) – Adaptive applications: (transcoding proxies, adaptive resource management) – Location sensing – Resource discovery (e.g. print to closest printer)

Ubiquitous Computing Example

• Ubiquitous computing: John is leaving home to go and meet his
• friends. While passing the fridge, the fridge sends a message to his

shoe that milk is almost finished. When John is passing grocery store, sh e sends messa e t lasses hich dis la s “BUY milk” messa e shoe sends message to glasses which displays “BUY milk” message. John buys milk, goes home.

• Core idea: ubiquitous computing assistants that help John
• Issues:
• Issues:

– Sensor design (miniaturization, low cost) – Smart spaces – Invisibility (room million sensors, minimal user distraction) Invisibility (room million sensors, minimal user distraction) – Localized scalability (more distant, less communication) – Uneven conditioning – Context-awareness (assist user based on her current situation) – Cyber-foraging (servers augment mobile device) – Self-configuring networks

Summary/Relationships

• Systems perspective: nomadic and mobile are reactive, ubiquitous

is proactive

• Distributed systems + mobile computing research issues = mobile

computing

• Mobile computing + pervasive computing issues = pervasive

computing

• In this class, first part will be mobile/nomadic computing, then

ubiquitous computing part

Typical of Ubicomp App

Generic:

Gather sensor data Process sensor data (Intelligence) Assist User (Output)

Location-aware mobile computing apps

• Focus mostly on mobile and ubiquitous computing apps that use

y q p g pp Smart Phone and Internet connectivity.

• Example: Location-aware mobile computing apps. Issues:
• Entropy: Infering how close two facebook friends are based on

Entropy: Infering how close two facebook friends are based on locations mutually visited

• May not want all facebook friends to know exactly where I am
• Automatically anonymize location info

y y

• Fact: User is at Starbucks, 180 Main St, Worcester, MA
• Status update to friend A: Emmanuel is at “coffee shop”
• Status update friend B: Emmanuel is at “Starbucks, 180 Main St, Worcester”
• Algorithms to automatically generate status update (based on closeness)

Internet

The Internet as a data source for Location-aware apps

[ Identifying the Activities Supported by Locations with Community Authored [ Identifying the Activities Supported by Locations with Community-Authored Content , Dearman and Truong, Univ. of Toronto ] U t l ti X ld lik t k l ti b d i

• User at location X would like to make location-based queries

– What activities can I do here? – What’s a good close place to do X activity (e.g. soccer)

S f

• Solution: Yelp is a community-authored reviewer website for

restaurants, activities, etc

• Yelp has: activities + location + goodness of venues
• Scrape + mine yelp: augment with location as searchable tag

Location-Aware Apps

• Easier location check-in
• Ubicomp 2010 video p395

Context-Aware Search

[ Hapori: Context-based Local Search for Mobile Phones using Community Behavioral Modeling and Similarity, Nicholas D. Lane, Dartmouth College]

• Goal: Improves Internet search results using context, such as

weather, age, profile of user, time, location and profile of other users to improve search.

• Example: a teenager gets a completely different set of

recommendations from and elder.

Mobile Social Networking

• Partipatory sensing: Many people cooperating on a task

p y g y p p p g

• Classic example: Comparative shopping
• At CVS, ready to buy toothpaste. Is CVS price the best locally?
• Ph ne has s ft are t

er ther members f m net rk

• Phone has software to query other members of my network
• People at other local stores (Walmart, Walgreens, etc) respond

with prices

UCLA Partipatory Sensing Video

• Demo from UCLA

Mobile Social Networking

• Smart phones have many sensors cameras etc
• Smart phones have many sensors, cameras, etc
• Imagine ability to access other people’s phones: Phone Sensing
• Like a telescopic lens into different locations: Microblogging

I nte rne t

Sensing Human Behavior

[Social Sensing for Epidimiological Behavior Change, Anmol Madan et al, MIT Media Lab]

• Goal: infer how falling sick affects the [mobile/network] behaviors
• f human beings.
• Examples: Changes in call rates or visiting low entropy places

Examples: Changes in call rates or visiting low entropy places more could mean person is sick

• Statistics of number of calls, co-location, proximity, WLAN and

bluetooth entropy found to be good predictors of illness bluetooth entropy found to be good predictors of illness.

• Findings could be used as an early warning tool.
• If strong inference, then nurse could call the person

Energy Efficiency

• Most resources increasing exponentially except battery energy

g p y p y gy (ref. Starner, IEEE Pervasive Computing, Dec 2003)

• Strategies:
• Energy harvesting: Energy from vibrations, moving humans
• Scale down: Reduce image video resolutions to save energy

Scale down: Reduce image, video resolutions to save energy

• Better user interface: Estimate and inform user how long

each potential task will take

• E g: At current battery level you can either type your paper for
• E.g: At current battery level, you can either type your paper for

45 mins, watch video for 20 mins, etc

Networks for Ubicomp

• Developed countries (e.g. US, UK) have 4 main wide area

telecommunications networks (or backbones) – Internet – Telephone – Cable television Cellular phone – Cellular phone

• Most are hierarchical: divided into backbone and local loop
• Only some of these wide area networks in developing nations?
• Internet is main computing backbone

Wireless Networks Papers

• Characteristics of Web Content by Timmins et al
• Formats, sizes, etc of mobile web pages

H l S l N ki f M bil

• Haggle: Seamless Networking for Mobile

Applications by Su et al

• Framework that manages various available networks, speeds,

etc for user

• A First Look at Traffic on Smartphones Hossein

Falaki et al Falaki et al

• Analysis of measured smart phone traffic

Smart Home Infrastructure

[ ElectriSense: Single-Point Sensing Using EMI for Electrical Event Detection and Classification in the Home, Sidhant Gupta et al, Univ. of Washington]

• Goal: Activity detection around the home
• Many new appliances have a “soft switch”

y pp

• Proposed a sensor for homes, plugged into single point:
• Train first: captures electric signature of each appliance in home
• Can then detect device when appliance turned on in future

Can then detect device when appliance turned on in future

• Appliance signature was unique and usable at different time home

E.g: iMac signature is unique. Capture once, use many times

Energy efficiency

• Smart home: energy efficiency
• Ubicomp 2010 video p361

Wireless Networks Types

• Cellular Network: Wide area wireless network operated by

Sprint, Verizon, AT&T, etc. 1G (analog), 2G today’s network, 3G coming, 4G (in some labs)

• WLANs:

– Infrastructure networks: wired backbone (Internet) wireless Infrastructure networks: wired backbone (Internet), wireless last hop. E.g WPI wireless LAN, New: mesh networks – Ad hoc networks: all wireless, no backbone, no order known in advance E g few deployed examples futuristic in advance. E.g. few deployed examples.. .futuristic

• Bluetooth: Short range communications, printers, headsets, etc

WiM W d h h b d d h

• WiMax: Wide area high bandwidth
• Sensor networks: self-organizing network of large numbers of

cooperating sensors deployed inside phenomenon. E.g. even more

• futuristic. Many research projects

Wireless systems: evolution

cellular phones satellites wireless LAN cordless cellular phones satellites phones

1982: Inmarsat-A 1981: NMT 450 1980: CT0 1984: 1983: AMPS 1987: CT1+ 1989: CT 2 1988: Inmarsat-C 1986: NMT 900 CT1 1992: GSM 1994: DCS 1800 1992: Inmarsat-B Inmarsat-M 1998 1991: DECT 199x: proprietary 1997: IEEE 802.11 1991: D-AMPS 1991: CDMA 1993: PDC DCS 1800 2001: IMT 2000 1998: Iridium 1999: 802.11b, Bluetooth analogue 2000: GPRS 2000: IEEE 802.11a IMT-2000 digital

4G – fourth generation: when and how?

200?: Fourth Generation (Internet based)

Ref: Mobile Communications, 2nd edition

Wireless Networking Challenges

• Wireless networking issues

– Wireless spectrum scarcity (regulated)

• Low bandwidth, asymmetric, heterogeneous

– Higher error rates (10-3):

• multipath fading, noise (engines, microwaves), echos...
• Note: indoor channel is different from outdoor

– Higher delays, higher jitter

• Connection time: secs for GSM, > 0.1s other wireless

, – Moving users:

• Uncontrolled cell population, variable link quality

p p , q y

• Different points of attachment to network
• Frequent network disconnections (cell phone)

Wireless Networking Challenges

• Wireless networking issues (contd)

– Less secure and less robust

• (e.g. signal leakage)
• More easily stolen tampered with (drunk employees)

More easily stolen, tampered with (drunk employees) – Shared medium Wh ’ i

• Who’s turn to transmit, etc

– Tough to guarantee Quality of Service (QoS)

Wireless Measurement

• Previous versions of class covered wireless protocols, standards
• This version: brief coverage on wireless
• Usage: measurement studies of wireless LANs and mobile web

Usage: measurement studies of wireless LANs and mobile web, wireless mesh networks, etc

• Programmer perspectives: How to program Android apps for

wireless (WLAN bluetooth cellular) connectivity wireless (WLAN, bluetooth, cellular) connectivity

• Novel wireless frameworks for ubicomp, seamless

communications during roaming

Wireless Security

• Wireless signals leak beyond building confines
• Mobile devices designed to be carried around=> more prone to

theft or misplacement p

• Mobility: tracking perpetuators is hard
• Security standards like Wireless Encryption Protocol (WEP) have

significant demonstrated flaws significant demonstrated flaws

• Anderson: over 90% of security breaches caused by lapses in

physical security:

• Example: drunk employee at bar with laptop
• Example: drunk employee at bar with laptop

WLAN Vulnerabilities

• Protocol (e.g 802.11) vulnerabilities:

– Rogue APs: Attacker inserts access point, hijacks mobile nodes – Jamming: ISM bands prone to that, microwaves, etc – Induce congestions, collisions: Induce collisions, congestion disobey protocol Delay bad for multimedia congestion, disobey protocol. Delay bad for multimedia – Exhaustion: Keep sending packets to wireless node, prevent sleep modes, drain battery, DoS Packet header manipulation: e g sequence/ACK Nos – Packet header manipulation: e.g sequence/ACK Nos.

Wi-Fi Privacy Ticker

[Sunny Consolvo et al , Intel Labs Seattle , University of Washington] [ y , , y g ]

• Many wireless security/privacy breeches occur
• Many open problems. Some too hard to solve for now
• E am les:
• Examples:

– website A may send your information to website B without your knowledge – New google search sends typed characters BEFORE you hit enter

S l i Al h i f i b i i d l

• Solution: Alert to user when info is being transmitted unsecurely
• Ticker streams violations of user's pre-defined breeches
• “Breeches“ identified and importance customizable
• Wi-Fi Ticker increased user awareness about security
• Even highly techno-savvy learned about breeches

Final Words

• This is a special topics graduate class
• Special Topics: I have picked selected topics that are hot.
• Coverage is not complete

Coverage is not complete

• Graduate class so graduate level work/effort is expected
• Seminar style classes: You get out what you put into them

Homework

• Today: Sign up for papers to present
• Procedure: Sign up sheet passed around, simply sign
• Summaries of week 2 papers (Smart homes and healthcare): due

Summaries of week 2 papers (Smart homes and healthcare): due before next class

• Two weeks: decide project area and partners (if any)
• Project? Never too early to start thinking about project talking
• Project? Never too early to start thinking about project, talking

to me.